Density functional theory (DFT) is perhaps the most widely applied quantum chemistry method in molecular simulations due to its ability to accurately and efficiently model a wide range of molecular systems. Still, it has a major deficiency, namely the lack of nondynamic correlation. As a result, it can yield unreliable results for chemical reactions, radicals, excited states, and charge-transfers. These properties are very often the focus of biological-based research and development and can only be studied computationally with quantum mechanical based methods. In Phase I of this project, we developed an efficient self-consistent solution for a new DFT method called real-space correlation (RSC) that addresses this deficiency. In addition, our RSC-DFT implementation was shown to be very efficient, some 100 times faster than a prior implementation. Our Phase I results demonstrate that RSC not only excels in standard DFT test cases, but also overcomes some of DFT's known failures. The overall goal of this Phase II project is to make RSC available for the majority of DFT computations, including calculation of the energy and gradient for ground and excited electronic states. We will also reduce the computational cost of RSC even further such that it will be as efficient as conventional DFT. Our development will be validated through two applications of biological interest, where DFT is known to give poor results. Finally, RSC will be combined with our dispersion DFT implementation, , and the unified method will represent a substantial leap forward in DFT, allowing researchers to routinely and reliably study molecular systems that were heretofore not possible with current quantum chemistry based techniques. This will also allow Q-Chem to expand its market to new areas. PUBLIC HEALTH RELEVANCE: This project aims to implement a new DFT method in a computationally efficient manner. DFT is at the core of molecular modeling and is applied widely in biological research/development and in drug discovery. The improved DFT will significantly increase researchers'quality of work and extend the application scope of DFT.